Document Type : Original/Review Paper

Authors

• monireh azimi hemat ¹
• Ezat Valipour ²
• laya aliahmadipoor ³

¹ Department of Computer Engineering and information technology, Payame Noor University (PNU), Iran

² Department of Applied Mathematics, Faculty of mathematics and computer science, Shahid Bahonar University of Kerman

³ Department of Applied Mathematics, Faculty of Mathmatics and Computer, Shahid Bahonar University of Kerman, Pajoohesh square, Kerman, Iran

Abstract

Visual features extracted from images in content-based image retrieval systems are inherently ambiguous. Consequently, applying fuzzy sets for image indexing in image retrieval systems has improved efficiency. In this article, the intuitionistic fuzzy sets are used to enhance the performance of the Fuzzy Content-Based Image Retrieval (F-CBIR) system. To this aim, an Intuitionistic Fuzzy Content-Based Image Retrieval (IF-CBIR) is proposed by applying intuitionistic fuzzy generators on fuzzy sets. Due to the diversity of the intuitionistic fuzzy distance measure, several are assessed in IF-CBIR; in these assessments, the measure with higher performance is identified. Finally, the proposed IF-CBIR and the existing crisp CBIR and F-CBIR simulate on Corel 5K and Corel 10K databases. The results show that our proposed method has higher (10-15%) precision compared to the mentioned methods.

Keywords

• Image retrieval
• Feature extraction
• Fuzzy image retrieval
• Intuitionistic fuzzy image retrieval
• HSV color space

Main Subjects

• H.3. Artificial Intelligence